DESCRIPTION: (Applicant's Abstract) Opiate and opioid compounds act on opioid receptors to produce pharmacological effects, most notably analgesia and euphoria. Multiple opioid receptors have been demonstrated and mu, delta and kappa opioid receptors have been cloned. The applicant's long-term objectives are to understand the structure-function relationships of these receptors at molecular level. The goal of the proposed research is to characterize the binding pocket of the mu opioid receptor. This goal will be accomplished by examining how certain irreversible and reversible ligands of two chemical classes bind to the receptor at molecular level. Beta-funaltrexamine (b-FNA), a morphinan compound, is the irreversible ligand to be examined. Reversible ligands include morphinans (morphine and naltrexone) and fentanyl and congeners. These two classes of opioid compounds have been used extensively in humans and some are popular drugs of abuse. The specific aims are as follows: (1) to determine the covalent incorporation site of b-FNA in the mu opioid receptor; (2) to determine how morphinan compounds bind to the mu opioid receptor; (3) to determine how fentanyl and congeners bind to the mu receptor. Collaboration has been established with Dr. R. DesJarlais and Dr. C.E. Peishoff of SmithKline Beecham, who have constructed a molecular model of the human mu opioid receptor. Determination of the site of b-FNA covalent incorporation in the mu receptor provides an anchoring site for modeling of interaction of b-FNA and morphinans with the receptor. Since b-FNA is a fairly rigid compound, hypotheses can be generated as to which amino acid residues interact with certain essential functional groups of morphinans. Hypotheses will also be formulated for fentanyl compounds based on results on morphinans. These hypotheses will be tested by mutagenesis studies, which will be used to refine the model. In addition, Dr. K. Rice of NIH will provide ligand analogs with an important functional group removed or substituted, which are very useful for probing receptor-ligand interaction. With such integration of mutagenesis data and model simulation, a reasonable structural model of the mu receptor will emerge. The proposed research will provide valuable information which will not be available through any other methods, that is, the exact site in the receptor that interacts with a certain functional group in a ligand of known structure. The information, coupled with the ligand structure, will provide insights into the structure of the binding pocket of the mu opioid receptor, which will aid in the design of selective agonists and antagonists for prevention and treatment of drug abuse.